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1.6Monitoring Feature Flag Impact

Every feature flag should have associated metrics that answer:

Is the new code path working? (Error rate per flag state)
Is it performant? (Latency per flag state)
Is it better for users? (Business metrics per flag state)
Is it stable? (No degradation trend over time)

# Prometheus metrics for feature flag monitoring
from prometheus_client import Counter, Histogram

flag_requests = Counter(
    'feature_flag_requests_total',
    'Total requests per feature flag state',
    ['flag_name', 'flag_state', 'outcome']
)

flag_latency = Histogram(
    'feature_flag_latency_seconds',
    'Latency by feature flag state',
    ['flag_name', 'flag_state'],
    buckets=[0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0]
)

Feature flags are the foundation of production testing. They transform deployment from a risky event into a controlled experiment with measurable quality outcomes.